时滞纳米运动系统的多速率采样预测自抗扰控制

电容型纳米位置传感器在纳米伺服系统中得到了越来越多的应用.这类超高精度模拟传感器用于反馈信号时因较长的模数转换时间将带来明显的测量时滞.而这类数字纳米伺服系统也因硬件使其采样频率在处理高频干扰时受到带宽限制.本文针对测量时滞和高频干扰的挑战,提出一种带采样预测功能的多速率自抗扰控制器设计方法.首先建立了电容式位移传感器的纳米运动平台带有时滞的动力学模型.其次,基于该模型设计多率采样预测线性扩张状态观测器和多率反馈控制器.通过设计预测型观测器,适当选取观测器增益,消除时滞对状态观测的影响.另外,将输出预估器加入预测扩张状态观测器中重构采样点间系统输出值,从而在时滞系统中更好地估计和消除高频干扰,并给出了系统的稳定性分析.最后通过压电驱动纳米运动平台的实时控制实验验证本文提出控制器的有效性.     

Multi-rate digital redesign of cascaded and dynamic output feedback systems

In this paper, a new indirect digital redesign method is presented for multi-rate sampled-data control systems with cascaded and dynamic output feedback controllers. These analogue controllers are often pre-designed based on desirable frequency specifications, such as bandwidth, natural angular frequency, etc. To take advantage of the digital controller over the analogue controller, digital implementation of these analogue controllers are often desirable. As only measured input-output signals are available, an ideal state reconstructing algorithm is utilised to obtain the multi-rate discrete-time states of the original continuous-time system. Based on the Chebyshev quadrature method, the gains of the multi-rate cascaded and the output feedback digital controllers are determined from their continuous-time counterparts according to the different sampling rates employed in the different parts of the closed-loop system. As a result, the respective analogue controllers with the high-frequency and low-frequency characteristics can be implemented using the respective fast-rate sampling and slow-rate sampling digital controllers. Unlike the classical direct bilinear transform method, which is an open-loop direct digital redesign method, the proposed digital controllers take into account the state-matching of the original continuous-time closed-loop system and the digitally redesigned sampled-data closed-loop system. To further improve the state-matching performance, an improved digital redesign approach is also developed to construct the multi-rate cascaded and dynamic output feedback digital controllers. Illustrative examples are given to demonstrate the effectiveness of the developed methods.     

DoS攻击下基于多率采样的多智能体系统安全一致性

本 文 研 究 了 一 类 带 有 多 率 采 样 的 线 性 多 智 能 体 系 统(Multiagent Systems, MASs)在 拒 绝 服 务(Denial-of-Service, DoS)攻击下的安全一致性控制问题, 其中DoS攻击通常阻断智能体之间的信息传输. 本文将多 率采样在网络化控制系统中的结果推广到了多智能体系统, 并考虑了非理想通信网络环境. 首先, 通过引入一个匹 配机制来同步由多率采样引起的智能体不同状态分量的采样数据. 然后, 在DoS攻击下, 针对带有多率采样的线 性MAS提出了一个基于多率采样的安全一致性控制器. 通过使用李雅普诺夫稳定性理论和切换系统方法, 获得了 包含DoS 攻击持续时间以及攻击频率的安全一致性充分条件. 最后, 给出了一个仿真例子来验证所提方法的有效 性, 并给出了多率采样与单率采样机制的性能对比分析.     

输出多采样反馈控制器及系统稳定性

针对由连续被控对象和数字控制器构成的数字控制系统,将现有的线性系统输出多采样线性反馈数字控制器设计方法推广到非线性系统．并相应地研究了非线性输出多采样反馈控制器及摄动非线性系统．给出了这类非线性输出多采样数字控制系统及其摄动系统的稳定性和鲁棒性条件．     

On interval tracking performance evaluation and practical varying sampling ILC

This paperconsiders the evaluation of interval tracking error for sampled control performance and an associated sampling technique to enhance the tracking performance. The upper bounds of the tracking error profile of arbitrary sample interval for both the linear system and nonlinear system are first given. A practical sampled-data iterative learning control with varying sampling rates is proposed to ensure a prior given tolerant tracking error. In this control strategy, the inter-sample behaviour is checked to determine which intervals are not satisfactory when the given tracking performance at-sample time instants is satisfied, and then the sampling frequency for such intervals is increased. Both at-sample and inter-sample tracking performance are satisfied after enough learning iterations. Two examples are simulated to demonstrate the effectiveness of the proposed sampling strategy.     

基于音圈电机的波动压力载荷控制研究

为开展波动载荷下滑动电接触摩擦动力学与电流传导机理研究,需在滑动电接触实验机上模拟弓网压力载荷波动,为此设计了基于音圈电机的动态压力伺服控制器.在建立波动载荷伺服系统数学模型基础上,设计了基于音圈电机的改进自抗扰控制方案,给出了改进自抗扰控制器的具体设计方法,并通过与模糊RBF网络相结合,实现参数自整定.针对传统自抗扰控制、PID控制与改进型自抗扰控制进行了仿真对比分析,并对改进型自抗扰控制进行了实验测试.仿真以及实验研究表明,该控制策略具有良好的控制性能以及鲁棒性能,满足实验系统要求.     

Sampled-data extended state observer for uncertain nonlinear systems

In this paper, we present a sampled-data nonlinear extended state observer (NLESO) design method for a class of nonlinear systems with uncertainties and discrete time output measurement. To accommodate the inter-sample dynamics, an inter-sample output predictor is employed in the structure of the NLESO to estimate the system output in the sampling intervals, where the prediction is used in the proposed observer instead of the system output. The exponential convergence of the sampled-data NLESO is also discussed and a sufficient condition is given by the Lyapunov method. A numerical example is provided to illustrate the performance of the proposed observer.     

基于ESO观测的PMLSM速度系统设计

永磁同步直线电机（PMLSM）是一个非线性、强耦合的多变量系统,利用传统的控制策略很难满足控制系统的高性能指标。本文在自抗扰策略的基础上结合PMLSM的数学模型,以Matlab/Simulink为仿真平台,实现了自抗扰自定义建模并针对PMLSM速度伺服系统设计了ADRC控制系统,其中利用ADRC控制技术有效观测了系统中的动态耦合扰动,针对PMLSM的速度控制系统分别采用了串级一阶ADRC与＂ADRC＋PID＂组合算法进行了仿真验证。仿真结果表明该方法具有很好的动静态特性。     

电动伺服舵机系统中的迭代学习控制

电动伺服舵机控制系统采用全数字三环控制策略,分别为位置环、速度环和电流环;作为内环的电流环,应具有良好的稳态和动态特性,其输出电流要求快速准确地跟踪给定电流,以保证舵机控制系统高性能位置伺服的要求;在传统的增量式积分分离PI控制算法的基础上,引入-D型迭代学习控制前馈环节,提高了电流跟踪的快速性和跟踪精度,建立了系统的数学模型并在MATLAB上进行了系统仿真;仿真结果表明,引入D型迭代学习控制后,电流环的稳态和动态特性良好,保证了输出电流跟踪的快速性、精确性.     

IEEE 1451.0 standard based smart readout for multi-rate control of system

This paper presents a novel architecture for multi-rate control system with disturbance estimation and rejection using FPGA connected with sensors and actuators through IEEE 1451 standard. A signum function is used for estimation error correction. Estimated states are used to provide the control input at a rate higher or lower than the sample rate thus providing multi-rate control. An architecture is proposed to implement the proposed multi-rate controller in FPGA platform through IEEE 1451.0-2007 standard. The control scheme requires minimum analog hardware, namely comparator and digital to analog convertor and provides multi-bit resolution with multi-rate processing.     

Multi-rate dissipativity based control of process networks

An approach to multi-rate distributed control design for process networks is presented, where the local measurements, local control and controller communication are allowed to operate at different sampling rates. Dissipative systems theory is used to facilitate stability and performance analysis of the process network, based upon dynamic supply rates which have been lifted into a global sampling rate. Quadratic difference forms are used as supply rates and storage functions, leading to less conservative stability and performance conditions as compared to classical types of supply rates. These theoretical results are illustrated by a case study of a heat exchanger network.     

航天机电伺服系统的自抗扰控制

航天机电伺服系统作用是接收火箭控制系统的指令信号并带动空气舵或者喷管跟随指令信号运动,其在应用上的主要特点是负载特性变化大.传统的PID算法在航天机电伺服系统上的应用已经比较成熟,但是在空气舵或者喷管本身负载特性发生改变时,传统的PID算法的控制效果会明显下降.因此,本文建立了航天机电伺服系统柔性运动模型,并提出了将自...     

A hybrid fault prediction method for control systems based on extended state observer and hidden Markov model

Fault diagnosis and prediction for complex control systems rely either on the collection of rich data for training neural networks or on the system models and prior knowledge of faults. These methods are difficult to apply directly in complex integrated systems due to the large uncertainties in practical scenarios. A new fault diagnosis and prediction technique that is based on extended state observer (ESO) and a hidden Markov model (HMM) for control systems is proposed in this paper. Real-time and predictive information that is obtained by ESO of the active disturbance rejection control (ADRC) is utilized to improve the HMM method for the fault prediction of control systems with large uncertain disturbances. The proposed approach realizes a high recognition rate with a small demand for data, and the dependence on the system model is weak without prior knowledge of faults. Fault prediction of the control system output can be realized without additional sensors. The proposed solution is evaluated in simulations of an asynchronous servo motor control system against the traditional control method and the ADRC control. The results indicate that the proposed method performs well in fault prediction and outperforms the traditional method in terms of control when disturbances and failures occur.     

Product property and production rate control of styrene polymerization

A multivariable multi-rate nonlinear model predictive control (NMPC) strategy is applied to styrene polymerization. The NMPC algorithm incorporates a multi-rate Extended Kalman Filter (EKF) to handle state variable and parameter estimation. A fundamental model is developed for the styrene polymerization CSTR, and control of polymer properties such as number average molecular weight (NAMW) and polydispersity is considered. These properties characterize the final polymer distribution and are strong indicators of the polymer qualities of interest. Production rate control is also demonstrated. Temperature measurements are available frequently while laboratory measurements of concentration and molecular weight distribution are available infrequently with substantial time delays between sampling and analysis. Observability analysis of the augmented system provides guidelines for the design of the augmented disturbance model for use in estimation using the multi-rate EKF. The observability analysis links measurement sets and corresponding observable disturbance models, and shows that measurements of moments of the polymer distribution are essential for good estimation and control. The CSTR is operated at an open-loop unstable steady state. Control simulations are performed under conditions of plant-model structural mismatch and in the presence of parameter uncertainty and disturbances, and the proposed multi-rate NMPC algorithm is shown to provide superior performance compared to linear multi-rate and nonlinear single-rate MPC algorithms. The major contributions of this work are the development of the multi-rate estimator and the measurement design study based on the observability analysis.     

Disturbance rejection control of a fuel cell power plant in a grid-connected system

Interface of a fuel cell plant to power grid is challenging because of the high nonlinearities of the fuel cell plant and the power conditioning system (PCS). This paper focuses on the control of grid-connected solid-oxide fuel cell (SOFC) power plant that is subject to varying load and uncertain network parameters. To this end, Active Disturbance Rejection Control (ADRC) is utilized to improve the performance of the PCS consisting of a dc-dc converter and a dc-ac inverter. ADRC is used in the dc-dc converter to stabilize the dc link voltage and yield a robust performance against the nonlinearity. Used in the dc-ac inverter, ADRC eliminates the steady-state error and is insensitive to the high-frequency noise. Simulation results show that, for grid current control, ADRC achieves a more robust performance than the conventional proportional-integral (PI) controller. Moreover, the total harmonic distortions (THDs) of the output current controlled by ADRC are always below 5% in spite of the variation in the load demand and network parameters.     

System identification and distributed control for multi-rate sampled systems

System outputs with different sampling times may challenge traditional subspace identification methods to generate accurate process models and consequently provide model-based control systems that may not be very effective. The multi-rate identification problem is addressed by dividing the multi-rate sampled system into different subsystems, and a multi-rate distributed model predictive control technique is proposed to control such systems. The performance of the proposed method is evaluated and illustrated by modeling and controlling the Tennessee Eastman challenge problem.     

A composite fractional order active disturbance rejection control method for a class of uncertain systems with multiple disturbances

The existing active disturbance rejection control (ADRC) method may not provide sufficient disturbance rejection to multiple mismatched disturbances for the fractional order systems. In this paper, a composite disturbance rejection approach is developed for a class of fractional order uncertain systems, by synthesizing the fractional order ADRC (FOADRC) approach and a disturbance observer (DO)-based compensation scheme. Taking advantage of more disturbance information and a filter structure, an improved DO is developed to achieve precise estimation of disturbances in the presence of sensor noises. In addition, a state transformation is developed to convert the system into a simple integral chain model with only matched disturbances. Then a composite control law is designed to compensate the disturbances and provide satisfying dynamic performance. The efficiency of the proposed method is demonstrated by a numerical simulation and an actual servo control simulation, as well as the comparison with two kinds of the existing ADRC methods and the commonly used integral sliding mode control (I-SMC) method.     

Nonlinear predictive control of irregularly sampled multirate systems using blackbox observers

This work aims the development of an inferential nonlinear model predictive control (NMPC) scheme based on a nonlinear fast rate model that is identified from irregularly sampled multirate data, which is corrupted with unmeasured disturbances and measurement noise. The model identification is carried out in two steps. In the first step, a MISO fast rate nonlinear output error (NOE) model is identified from the irregularly sampled output data. In the second step, a time varying nonlinear auto-regressive (NAR) type model is developed using the residuals generated in the first step. The deterministic and stochastic components of the observer are parameterized using generalized ortho-normal basis filters (GOBF). The identified NOE and NAR models are combined to form MISO state observers. We then proceed to use these identified observers to formulate a nonlinear MPC strategy for controlling irregularly sampled multirate systems. The identified observers are used to generate inter-sample estimates of the irregularly sampled outputs and for performing future trajectory predictions. The efficacy of the proposed modeling and control scheme is demonstrated using simulations on a benchmark continuous fermentation process. This process exhibits input multiplicity and change in the sign of steady state gain in the operating region. The validity of the proposed modeling and control scheme is also established by conducting identification and control experiments on a laboratory scale heater-mixer setup. The proposed NMPC gives satisfactory regulatory as well as servo performance over a wide operating range in the irregularly sampled multirate scenario.     

Time delay and sampling rate effect on dual-stage servo control performance

Dual-stage servo control loops are modeled for hard disk drives (HDDs) with the consideration of time delay which is due to the time taken for position error signal measurement and controller computing. The time delays are involved in controller design and the closed servo control loop is investigated to show the effects of the time delay on servo control performance. The studied actuation system is a PZT milliactuator based dual-stage servo system. The delay time within and over the sampling interval is separately considered for 62.5 kHz sampling rate. To show the effect of sampling rate on servo control performance, a control system designed with 40 kHz sampling rate is also studied. As a result, significant improvement of servo performance is attained with this increased sampling rate and a reasonable time delay for the dual-stage actuation system.     

State covariance assignment for sampled-data feedback control systems

This paper proposes a new performance criterion of ‘covariance’ for sampled-data systems. A covariance of sampled-data systems is defined by taking account of inter-sample behaviour. An SCA (state covariance assignment) problem for sampled-data feedback control systems is also discussed, which is the counterpart of that for purely continuous or discrete-time feedback control systems. The SCA problem for sampled-data systems will be solved as a discrete-time SCA problem, where the discretization preserves the state covariance and is in two steps. In the first step, a certain sample time performance is required to ensure the inter-sample performance, and the output signal results to be discretized. The second step is to discretize the input signal.